中草药

中医药调控免疫代谢机制研究进展

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中草药 | 综述 2026,57(7): 2809-2824

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中草药 |综述 2026 , 57 (7) : 2809 -2824

中医药调控免疫代谢机制研究进展

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田子琦¹, 宋志前¹, 林涛¹, 王淳¹, 杨丰赫¹, 贺乔¹, 王琛¹, 宁张弛¹

作者信息

通讯作者:

王琛

作者简介:

田子琦: 田子琦,硕士,初级技师,从事中药及复方物质基础研究。E-mail:tchenxiao897@163.com

Research progress on mechanism of traditional Chinese medicine regulating immune metabolism

TIAN Ziqi, SONG Zhiqian, LIN Tao, WANG Chun, YANG Fenghe, HE Qiao, WANG Chen, NING Zhangchi

Affiliations

doi: 10.7501/j.issn.0253-2670.2026.07.030

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摘要

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免疫代谢网络的动态平衡是维系机体稳态的核心，免疫细胞功能重塑与代谢重编程的紧密互作在疾病发生发展中扮演关键角色。中医药秉持“整体调控、辨证施治”的核心特色，其多成分、多靶点的作用优势与免疫代谢网络的系统性调控需求高度契合。系统综述了高通量测序、单细胞代谢组学、代谢流分析等现代技术在中医药免疫代谢研究中的应用范式，重点阐述中药单体（黄酮、多糖、皂苷等）及复方对巨噬细胞、T细胞、树突状细胞、B细胞、中性粒细胞等核心免疫细胞的代谢调控机制，同时剖析了当前研究中存在的细胞类型研究不均衡、有效成分与靶点网络模糊、中医“证型”与代谢表型脱节等瓶颈，提出多组学技术整合、人工智能辅助靶点预测、“证型-代谢表型”关联分析等创新研究方向，为中医药现代化及免疫相关疾病的代谢调控治疗提供科学依据与实践参考。

关键词

免疫代谢 / 代谢重编程 / 免疫代谢研究技术 / 多组学技术整合 / 人工智能辅助靶点预测 / “证型-代谢表型”关联分析 / 代谢调控

Abstract

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The dynamic balance of the immunometabolic network constitutes the core of maintaining organismal homeostasis, and the close crosstalk between immune cell functional remodeling and metabolic reprogramming exerts a pivotal regulatory role in the occurrence and progression of diseases. Adhering to the core characteristic of holistic regulation and treatment based on syndrome differentiation, traditional Chinese medicine (TCM) features the inherent advantages of multi-component and multi-target actions, which are highly consistent with the systematic regulatory demands of the immunometabolic network. This paper systematically reviews the application paradigms of modern technologies including high-throughput sequencing, single-cell metabolomics and metabolic flux analysis in TCM immunometabolism research, and focuses on elaborating the metabolic regulatory mechanisms of TCM monomers (flavonoids, polysaccharides, saponins, etc.) and compound prescriptions on core immune cells such as macrophages, T cells, dendritic cells, B cells and neutrophils. Meanwhile, it analyzes the key bottlenecks in current research, including the unbalanced research on immune cell subtypes, ambiguous correlation between active components and target networks, and the disconnection between TCM syndrome types and metabolic phenotypes. Furthermore, innovative research directions are proposed, such as multi-omics technology integration, artificial intelligence-assisted target prediction and correlation analysis of syndrome type-metabolic phenotype, so as to provide a scientific basis and practical reference for the modernization of TCM and the metabolic regulatory therapy for immune-related diseases.

Key words

immunometabolism / metabolic reprogramming / immunometabolism research techniques / multi-omics technology integration / artificial intelligence-assisted target prediction / “syndrome type-metabolic phenotype” association analysis / metabolic regulation

引用本文

田子琦, 宋志前, 林涛, 王淳, 杨丰赫, 贺乔, 王琛, 宁张弛. 中医药调控免疫代谢机制研究进展. 中草药, 2026 , 57 (7) : 2809 -2824 . DOI: 10.7501/j.issn.0253-2670.2026.07.030

TIAN Ziqi, SONG Zhiqian, LIN Tao, WANG Chun, YANG Fenghe, HE Qiao, WANG Chen, NING Zhangchi. Research progress on mechanism of traditional Chinese medicine regulating immune metabolism[J]. Chinese Traditional and Herbal Drugs, 2026 , 57 (7) : 2809 -2824 . DOI: 10.7501/j.issn.0253-2670.2026.07.030

基金

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国家重点研发计划中医药现代化青年科学家项目 (2025YFC3509500); 中央级公益性科研院所基本科研业务费专项资金资助 (YZX-202402,YPX-202307,YZX-202334)

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2026年第57卷第7期

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doi: 10.7501/j.issn.0253-2670.2026.07.030

接收时间：2025-11-20
首发时间：2026-09-09

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2种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

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